code: def test_create_proportional_tensor():
      axis_weights = [
          np.array([1, 2], np.float64),
          np.array([5, 15, 7], np.float64),
      ]
      tensor = _create_proportional_tensor(axis_weights)
      # geometric mean is 9, so each should sum to that
      expected = np.array(
          [
              [0.55555556, 1.66666667, 0.77777778],
              [1.11111111, 3.33333333, 1.55555556],
          ]
      )
      assert np.allclose(tensor, expected)
  
file_path: interpret/python/interpret-core/tests/glassbox/ebm/test_ebm_utils.py
imports: from math import ceil, floor
  from interpret.glassbox._ebm._utils import make_bag, convert_categorical_to_continuous, _create_proportional_tensor, deduplicate_bins
  import numpy
  import pytest
label_desc: Use image node_id 7 for calling a global function with example usage: test_create_proportional_tensor() without return types